Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition [PDF]
Computer Vision and Pattern Recognition, 2021 Visual Place Recognition is a challenging task for robotics and autonomous systems, which must deal with the twin problems of appearance and viewpoint change in an always changing world.
Stephen Hausler +4 more
semanticscholar +1 more source
Updates to the DScribe library: New descriptors and derivatives. [PDF]
Journal of Chemical Physics, 2023 We present an update of the DScribe package, a Python library for atomistic descriptors. The update extends DScribe's descriptor selection with the Valle-Oganov materials fingerprint and provides descriptor derivatives to enable more advanced machine ...
J. Laakso +6 more
semanticscholar +1 more source
Negative Patient Descriptors: Documenting Racial Bias In The Electronic Health Record
Health Affairs, 2022 Little is known about how racism and bias may be communicated in the medical record. This study used machine learning to analyze electronic health records (EHRs) from an urban academic medical center and to investigate whether providers’ use of negative ...
Michael Sun +3 more
semanticscholar +1 more source
You Only Hypothesize Once: Point Cloud Registration with Rotation-equivariant Descriptors [PDF]
ACM Multimedia, 2021 In this paper, we propose a novel local descriptor-based framework, called You Only Hypothesize Once (YOHO), for the registration of two unaligned point clouds.
Haiping Wang +4 more
semanticscholar +1 more source
HPatches: A Benchmark and Evaluation of Handcrafted and Learned Local Descriptors [PDF]
Computer Vision and Pattern Recognition, 2017 In this paper, we propose a novel benchmark for evaluating local image descriptors. We demonstrate that the existing datasets and evaluation protocols do not specify unambiguously all aspects of evaluation, leading to ambiguities and inconsistencies in ...
Vassileios Balntas +3 more
semanticscholar +1 more source
Machine Learning Descriptors for Data‐Driven Catalysis Study
Advancement of science, 2023 Traditional trial‐and‐error experiments and theoretical simulations have difficulty optimizing catalytic processes and developing new, better‐performing catalysts.
Li-Hui Mou +4 more
semanticscholar +1 more source
RIGA: Rotation-Invariant and Globally-Aware Descriptors for Point Cloud Registration [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Successful point cloud registration relies on accurate correspondences established upon powerful descriptors. However, existing neural descriptors either leverage a rotation-variant backbone whose performance declines under large rotations, or encode ...
Hao Yu +7 more
semanticscholar +1 more source
Learning General and Distinctive 3D Local Deep Descriptors for Point Cloud Registration [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 An effective 3D descriptor should be invariant to different geometric transformations, such as scale and rotation, robust to occlusions and clutter, and capable of generalising to different application domains. We present a simple yet effective method to
Fabio Poiesi, Davide Boscaini
semanticscholar +1 more source
Keywords given by authors of scientific articles in database descriptors [PDF]
, 2007 This paper analyses the keywords given by authors of scientific articles and the descriptors assigned to the articles in order to ascertain the presence of the keywords in the descriptors.
Alonso-Arroyo, Adolfo +3 more
core +1 more source
, 2022 all-descriptors.csv collects all physico-chemical descriptors of antimicrobials extracted from QSAR, QM, and MD ...
Giuliano Malloci (2060875) +5 more
core +1 more source